Machines such as, for example, dozers, motor graders, wheel loaders, wheel tractor scrapers, and other types of heavy equipment are used to perform a variety of tasks at a worksite. Autonomously and semi-autonomously controlled machines are capable of operating with little or no human input by relying on information received from various machine systems. For example, based on machine movement input, terrain input, and/or machine operational input, a machine can be controlled to remotely and/or automatically complete a programmed task. By receiving appropriate feedback from each of the different machine systems during performance of the task, continuous adjustments to machine operation can be made that help to ensure precision and safety in completion of the task. In order to do so, however, the information provided by the different machine systems should be accurate and reliable. Parameters indicative of machine motion, e.g., velocity and change in position of the machine, are parameters whose accuracy may be important for control of the machine and its operation.
Some exemplary systems determine velocity and change in position based on vision systems, utilizing methods known as visual odometry. For example, an exemplary system that may be used to determine changes in position using visual-odometry techniques is disclosed in U.S. Patent Publication No. 2014-0300732 to Friend et al. that published on Oct. 9, 2014 (the '732 publication). The system of the '732 publication fuses images from a camera and a Light Detection and Ranging (LIDAR), and utilizes these images to determine rotation and translation velocities for a machine.
Although the system of the '732 publication may be useful for determining the rotation and translation velocities of a machine using visual-odometry techniques, the '732 publication does not describe techniques for estimating an error associated with the visual-odometry system outputs (e.g., rotation and translation velocities). Knowing an error estimate associated with the visual-odometry system outputs is desirable because knowledge of the error estimate may allow more accurate determination of a position of the machine. For example, knowledge of an error estimate may allow the fusing of the visual-odometry system outputs with outputs from other sensors, such as an inertial measurement unit.
The disclosed motion determination system is directed to overcoming one or more of the problems set forth above and/or other problems of the prior art.